Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.
Digital Object Identifier (DOI) : 10.14569/IJARAI.2012.010406
Article Published in International Journal of Advanced Research in Artificial Intelligence(IJARAI), Volume 1 Issue 4, 2012.
Abstract: It is through experience one could as certain that the classifier in the arsenal or machine learning technique is the Nearest Neighbour Classifier. Automatic melakarta raaga identification system is achieved by identifying the nearest neighbours to a query example and using those neighbours to determine the class of the query. This approach to classification is of particular importance today because issues of poor run-time performance are not such a problem these days with the computational power that is available. This paper presents an overview of techniques for Nearest Neighbour classification focusing on; mechanisms for finding distance between neighbours using Cosine Distance, Earth Movers Distance and formulas are used to identify nearest neighbours, algorithm for classification in training and testing for identifying Melakarta raagas in Carnatic music. From the derived results it is concluded that Earth Movers Distance is producing better results than Cosine Distance measure.
B Tarakeswara Rao, Sivakoteswararao Chinnam, P Lakshmi Kanth and M.Gargi, “Automatic Melakarta Raaga Identification Syste: Carnatic Music” International Journal of Advanced Research in Artificial Intelligence(IJARAI), 1(4), 2012. http://dx.doi.org/10.14569/IJARAI.2012.010406